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Keivan Faghih Niresi

Expertise

Computational sensing/imaging, Inverse problems, Signal processing, Graph neural networks, Domain adaptation.
Keivan is a PhD student at école Polytechnique Fédérale de Lausanne (EPFL). He joined the Intelligent Maintenance and Operations Systems (IMOS) Lab under the supervision of Prof. Olga Fink in February 2023.
Prior to joining EPFL, he obtained his master's degree from the Institute of Communications Engineering, College of Electrical Engineering and Computer Science, National Tsing Hua University (NTHU) where he conducted research in convex and non-convex optimization, statistical signal processing, deep learning, and hyperspectral imaging under the supervision of Prof. Chong-Yung Chi. He also had the opportunity to work as a machine learning engineer intern at PranaQ, where he focused on developing signal processing and feature extraction algorithms for biomedical signals such as photoplethysmogram (PPG) and electrocardiogram (ECG).

Education

Master of Science

| Communications Engineering

2020 – 2022 National Tsing Hua University

Bachelor of Science

| Electrical Engineering

2015 – 2019 University of Guilan

Selected publications

Efficient Unsupervised Domain Adaptation Regression for Spatial-Temporal Sensor Fusion

Keivan Faghih Niresi
Published in IEEE Internet of Things Journals in 2025

Physics-Enhanced Graph Neural Networks for Soft Sensing in Industrial Internet of Things

Keivan Faghih Niresi, Hugo Bissig, Henri Baumann, Olga Fink
Published in IEEE Internet of Things Journal in 2024

Robust Hyperspectral Inpainting via Low-Rank Regularized Untrained Convolutional Neural Network

Keivan Faghih Niresi, Chong-Yung Chi
Published in IEEE Geoscience and Remote Sensing Letters in 2023

Unsupervised Hyperspectral Denoising Based on Deep Image Prior and Least Favorable Distribution

Keivan Faghih Niresi, Chong-Yung Chi
Published in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing in 2022

Teaching & PhD

CIVIL-332

Data Science for infrastructure condition monitoring
Course Book

CIVIL-426

Machine learning for predictive maintenance applications
Course Book